GCTA.rr: GCTA: Genome-wide complex trait analysis

In wal615/prime.total.effect: Total effect estimation of the environmental mixtures

Description

GCTA.rr calculates the total effect of the exposure of the environmental mixture.

To estimate the the total effect, we use a method called GCTA. Genome-wide complex trait analysis (GCTA) Genome-based restricted maximum likelihood (GREML) is a statistical method for variance component estimation in genetics which quantifies the total narrow-sense (additive) contribution to a trait's heritability of a particular subset of genetic variants. More details of GCTA could be found in here. More details of total effect estimation and how it can be applied to mixtures can be found in the here.

Usage

GCTA.rr(x, y, target = c("beta2", "r2")[1], bs.iter = 1000, verbose = TRUE)

Arguments

x	A numeric matrix.
y	A continuous vector.
target	A character value. beta2 is for the total effect and r2 is for the the proportion of the variance explained x.
bs.iter	A numeric value. The number of iterations of bootstrap for variance estimation.
verbose	A boolean variable. If TRUE, then the function will print the process of bootstrap.

Value

A list. If target = r2,

1. r2: Estimated the proportion of the variance explained x, which is the proportion of the variance in a health outcome that is predictable from the environmental mixtures

2. r2.var: Estimated variance of the proportion of the variance explained x, calculated by a bootstrap resampling procedure

3. r2.bs.raw: The raw bootstrap sampling result

If target = beta2,

1. beta2: Estimated total effect.

2. beta2.var: Estimated variance of the total effect via a bootstrap procedure

3. beta2.bs.raw: The raw bootstrap sampling result

wal615/prime.total.effect documentation built on April 29, 2020, 2:05 p.m.